Viral Marketing in Social Network Using Data Mining

Data mining is a process of analyzing data from different perspectives and summarizing it into useful information .The proposed work focus on clustering application which is "Collaborative Data mining "which mines different subgroups from some networks in the form of graph such as a social network. In this work using social network, two type of clusters are developed using data mining algorithms, one having strong tie and other having a weak tie between members and then the cluster with strong tie is used for discovering the highly influential node for viral advertising using target marketing to increase the profit with less advertising expense

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

We study the problem of large-scale network embedding, which aims to learn latent representations for network mining applications. Previous research shows that 1) popular network embedding benchmarks, such as DeepWalk, are in essence implicitly factorizing a matrix with a closed form, and 2)the explicit factorization of such matrix generates more powerful embeddings than existing methods. However, directly constructing and factorizing this matrix---which is dense---is prohibitively expensive in terms of both time and space, making it not scalable for large networks. In this work, we present the algorithm of large-scale network embedding as sparse matrix factorization (NetSMF). NetSMF leverages theories from spectral sparsification to efficiently sparsify the aforementioned dense matrix, enabling significantly improved efficiency in embedding learning. The sparsified matrix is spectrally close to the original dense one with a theoretically bounded approximation error, which helps maintain the representation power of the learned embeddings. We conduct experiments on networks of various scales and types. Results show that among both popular benchmarks and factorization based methods, NetSMF is the only method that achieves both high efficiency and effectiveness. We show that NetSMF requires only 24 hours to generate effective embeddings for a large-scale academic collaboration network with tens of millions of nodes, while it would cost DeepWalk months and is computationally infeasible for the dense matrix factorization solution. The source code of NetSMF is publicly available (https://github.com/xptree/NetSMF).Comment: 11 pages, in Proceedings of the Web Conference 2019 (WWW 19

Impoliteness across Online Platforms

Το Ίντερνετ και τα διάφορα μέσα κοινωνικής δικτύωσης συνιστούν ένα χώρο όπου οι χρήστες ασκούν την ελευθερία λόγου συμμετέχοντας σε πολυφωνικές συνομιλίες. Το να έχει κανείς τη δυνατότητα να εκφράζεται ελεύθερα είναι αναγκαίο σε κάθε συνδιαλλαγή, ωστόσο υπάρχει η πιθανότητα να προκαλέσει απειλητική προς το πρόσωπο συμπεριφορά. Πράγματι, η αγένεια δεν λείπει από τη διαδικτυακή επικοινωνία, ιδιαίτερα όταν τα υπό συζήτηση θέματα είναι αμφιλεγόμενα. Η παρούσα έρευνα έχει σκοπό να εξετάσει το λόγο τριών μέσων κοινωνικής δικτύωσης (δηλαδή του Twitter, του YouTube και του Reddit) και να διαπιστώσει εάν τα ιδιαίτερα χαρακτηριστικά του κάθε μέσου επηρεάζουν την αγένεια μεταξύ των χρηστών τους. Για το σκοπό αυτό, επικεντρώνομαι σε ένα θέμα συζήτησης, εκείνο που αφορά τις πυρκαγιές του Ιουλίου 2018 στην Αττική. Χρησιμοποιούνται ποιοτικές αλλά και ποσοτικές μέθοδοι καθώς ο συνδυασμός τους πιστεύεται ότι έχει μεγάλα οφέλη για μια τέτοια ανάλυση. Συγκροτήθηκαν τρία σώματα κειμένων, ένα για κάθε μέσο που μελετάται. Μικρά αλλά αντιπροσωπευτικά δείγματα αναλύθηκαν ποιοτικά σύμφωνα με τις δύο κύριες κατηγορίες αγένειας: εκείνη που προκύπτει από τη χρήση υπονοημάτων, τη συμβατικοποιημένη (τυποποιημένη) αγένεια και τις υποκατηγορίες τους. Επιπλέον, με τη βοήθεια υπολογιστικών εργαλείων, υβριστικές λέξεις-κλειδιά εξήχθησαν και από τα τρία σώματα κειμένων και αναλύθηκαν συγκριτικά. Αυτή η από κοινού ανάλυση αποκάλυψε πως το YouTube εμπεριέχει αρκετή (συμβατικοποιημένη) αγένεια, κάτι που ίσως οφείλεται σε παράγοντες όπως η απουσία οποιουδήποτε συντονισμού, ορίου έκτασης των αναρτήσεων και λεπτομερών προφίλ όπως επίσης η παρουσία των βίντεο ως ερέθισμα για τη συνδιαλλαγή. Το Twitter ακολουθεί δεύτερο όσον αφορά την απειλητική προς το πρόσωπο συμπεριφορά που παρατηρείται μεταξύ των χρηστών του, πιθανότατα λόγω του διττού σκοπού για τον οποίο χρησιμοποιήθηκε, αρχικά για να ενημερώσει και αργότερα για να ασκήσει κριτική, αλλά και λόγω του περιορισμού των αναρτήσεων σε 280 χαρακτήρες, της μόνιμης προβολής των αναρτήσεων ενός χρήστη στο προφίλ του, της απουσίας συντονισμού, της εκτενούς χρήσης της πολυτροπικότητας και άλλων εγγενών παροχών του Twitter όπως είναι για παράδειγμα τα hashtags. Σημαντικά λιγότερη αγένεια παρατηρήθηκε στο Reddit, η φύση του οποίου το καθιστά χώρο που φιλοξενεί κυρίως πολιτισμένο διάλογο. Ο αριθμός των αγενών αναρτήσεων με χρήση υπονοημάτων ξεπέρασε εκείνον των αναρτήσεων με συμβατικοποιημένη αγένεια, εξαιτίας της ύπαρξης έντονου συντονισμού και δημόσιων προφίλ καθώς και εξαιτίας του μεγέθους και της συνεκτικότητας της κοινότητας των χρηστών. Συμπεραίνεται ότι, με βάση τα χαρακτηριστικά τους, τα μέσα κοινωνικής δικτύωσης φαίνεται να προσελκύουν μια συγκεκριμένη βάση χρηστών με ιδιαίτερα κίνητρα και νοοτροπία, στοιχείο που με τη σειρά του διαμορφώνει και την αγένεια που παρατηρείται στα μέσα αυτά.The Internet and the various social media platforms constitute a space where users exercise their right to free speech by participating in polylogues. Being able to speak one’s mind is essential in interactions, though it may provoke face-threatening behavior. In fact, impoliteness is not that rare in online communication, especially when highly contentious issues are discussed. The aim of this work is to examine discourse across three online social media platforms (i.e. Twitter, YouTube and Reddit) and attempt to determine whether the individual features of the platforms have an impact on the amount and form of impoliteness employed by their users. To this end, I concentrate on a single topic, that of the July 2018 wildfires in Attica, Greece. Both qualitative and quantitative approaches are followed since their combination is believed to offer great benefits to any kind of analysis. Three corpora were compiled, one for each of the platforms studied. Small but representative samples of them were qualitatively analyzed on the basis of the two major impoliteness types: implicational and conventionalized, and their subcategories. In addition, swearword keywords were extracted by means of corpus analysis tools and analyzed comparatively across the three corpora. This joint analysis revealed that YouTube involved a great deal of (conventionalized) impoliteness which could be due to factors such as the total absence of moderation, of post length limit and of detailed personal profiles as well as the presence of videos as stimuli for interaction. Twitter was second in terms of the amount of face-threatening behavior observed among its users, probably influenced by the dual purpose of its use, which was initially to inform and later to criticize, the 280-character restriction on tweets, the permanent display of posts on one’s profile, the lack of moderation, the extensive use of multimodality and other inherent Twitter affordances like hashtags. Considerably less impoliteness was found on Reddit, whose forum-like nature makes it a place that mostly invites civil interaction. Implicationally impolite posts outnumbered conventionally impolite ones, perhaps owing to the heavy moderation, the existence of public profiles and the size and coherence of the user community. It is concluded that, due to their characteristics, platforms seem to attract a certain userbase with its own motives and mindset, which in turn shape the impoliteness found within them

#Présidentielle2017 : a critical discourse analysis of the 2017 French presidential campaign on Twitter

In the context of the 2017 French presidential election, this dissertation examines political discourse on Twitter from a socio-semiotic perspective. Specifically, it focuses on campaign tweets as a unique genre of discourse that plays a pivotal role in the dissemination and amplification of political discourse. This study uses an innovative framework which combines two approaches to discourse analysis: Critical Discourse Analysis (CDA) and Systemic Functional Linguistics (SFL). CDA and SFL are socially-oriented approaches to discourse which share a dialectical view of text-in-context whereby discourse shapes and is shaped by the social and cultural context in which it occurs (Fairclough, 2003; Hasan, 2014). I draw on Norman Fairclough’s concept of ‘order of discourse’, which refers to a unique configuration of genres, discourses and styles constitutive of a social practice or structure (Fairclough, 1993). I suggest that digital campaigning constitutes a growing social practice with its own order of discourse, and I examine how the 2017 presidential candidates mobilized particular discursive mechanisms to realize a variety of discourses (ideologies) and styles (identities). In addition, I analyze how they exploited the generic affordances and constraints of tweets to their advantage. To this end, I collected a total of 208 tweets from six main actors of the 2017 election: outgoing president François Hollande and candidates Emmanuel Macron, Marine Le Pen, François Fillon, Jean-Luc Mélenchon and Benoît Hamon. All tweets were posted in reaction to three events of significance for the election. This dissertation provides an in-depth, multifunctional analysis that focuses on ideational, interpersonal and textual ways of meaning-making: (1) transitivity and social actor representation, (2) modality and engagement and (3) texture and generic structure. I argue that the 2017 election was above all characterized by an effort of the candidates to distance themselves from the political class. I suggest that this antiestablishment sentiment was realized by two ‘styles of politics’: the populist style and the centrist style. Finally, I argue that the structural constraints of tweets amplify these populist appeals through the combination of decontextualization and semantic condensation.French and Italia

Gendered migrations : an exploration of the influence of migration on Polish women's perception of gender roles

Following the expansion of the European Union (EU) in 2004, migration from the newAccession 8 EU Member States to the United Kingdom (UK) has been identified as one of themost significant international migratory movements to the UK in recent times. The largestmember of these states is Poland and the UK has been the most common destination for Polishmigrants post 2004. Arguably, there is limited literature that focuses solely on women; indeed,women migrants were invisible until the 1970s. In relation to A8 migration, gender and genderroles are an under-researched area. The aim of this thesis is to fill this gap and offer new insightswith regard to the influence of the migratory experience on Polish women’s lives and the waythey negotiate their gender roles through migration. This thesis contributes new and uniqueevidence to the debates surrounding migration, gender, Polish women and comparative socialpolicy, in particular with regard to the role of networks in migration; enduring and new pushand pull factors; the icon of ‘Matka Polka’ and work-life balance.Through the use of 32 qualitative in-depth semi-structured interviews with Polish migrantwomen resident in two countries – the UK and Poland, this thesis considers the factors thatmotivate the initial and any subsequent ‘return’ international migratory movements undertakenby Polish women between the UK and Poland. Additionally, the ways in which Polish migrantwomen (re)negotiate their gender roles in regard to paid work and informal familial care acrosstime and space are explored. It is concluded that motivations for migration as well as motivesto remain in the host country are often related to economic factors and the availability of migrantnetworks. It is shown that the migratory process may indeed influence women’s perception ofgender roles which seem to be re-evaluated post migration